docstr: forward.
  :param x: torch.Tensor, input tensor with input size (B, C, T, H, W).
docstr_tok: ["forward",".",":","param","x",":","torch.Tensor",",","input","tensor","with","input","size","(","B",",","C",",","T",",","H",",","W",")","."]
code: def forward(self, x):
      """forward.
      :param x: torch.Tensor, input tensor with input size (B, C, T, H, W).
      """
      residual = x
      out = self.conv1(x)
      out = self.bn1(out)
      out = self.relu1(out)
      out = self.conv2(out)
      out = self.bn2(out)
      if self.downsample is not None:
          residual = self.downsample(x)
  
      out += residual
      out = self.relu2(out)
  
      return out
  
file_path: audio/examples/avsr/models/resnet.py
imports: import torch.nn
label_desc: Use image node_id 2 for calling the BasicBlock obj's underlying member method code with example usage: obj.forward(x) and returns: out